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Trapit Bansal
Trapit Bansal
OpenAI
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Title
Cited by
Cited by
Year
Emergent complexity via multi-agent competition
T Bansal, J Pachocki, S Sidor, I Sutskever, I Mordatch
arXiv preprint arXiv:1710.03748, 2017
4922017
Continuous adaptation via meta-learning in nonstationary and competitive environments
M Al-Shedivat, T Bansal, Y Burda, I Sutskever, I Mordatch, P Abbeel
arXiv preprint arXiv:1710.03641, 2017
4212017
Ask the GRU: Multi-task learning for deep text recommendations
T Bansal, D Belanger, A McCallum
Proceedings of the 10th ACM Conference on Recommender Systems, 107-114, 2016
3892016
A2N: Attending to neighbors for knowledge graph inference
T Bansal, DC Juan, S Ravi, A McCallum
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
1422019
Learning to few-shot learn across diverse natural language classification tasks
T Bansal, R Jha, A McCallum
arXiv preprint arXiv:1911.03863, 2019
1142019
Content driven user profiling for comment-worthy recommendations of news and blog articles
T Bansal, M Das, C Bhattacharyya
Proceedings of the 9th ACM Conference on Recommender Systems, 195-202, 2015
922015
Self-supervised meta-learning for few-shot natural language classification tasks
T Bansal, R Jha, T Munkhdalai, A McCallum
arXiv preprint arXiv:2009.08445, 2020
882020
Marginal likelihood training of BiLSTM-CRF for biomedical named entity recognition from disjoint label sets
N Greenberg, T Bansal, P Verga, A McCallum
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
872018
Unsupervised pre-training for biomedical question answering
V Kommaraju, K Gunasekaran, K Li, T Bansal, A McCallum, I Williams, ...
arXiv preprint arXiv:2009.12952, 2020
582020
A provable SVD-based algorithm for learning topics in dominant admixture corpus
T Bansal, C Bhattacharyya, R Kannan
Advances in neural information processing systems 27, 2014
572014
Diverse distributions of self-supervised tasks for meta-learning in NLP
T Bansal, K Gunasekaran, T Wang, T Munkhdalai, A McCallum
arXiv preprint arXiv:2111.01322, 2021
552021
Relnet: End-to-end modeling of entities & relations
T Bansal, A Neelakantan, A McCallum
arXiv preprint arXiv:1706.07179, 2017
352017
Going beyond corr-lda for detecting specific comments on news & blogs
MK Das, T Bansal, C Bhattacharyya
Proceedings of the 7th ACM international conference on Web search and data …, 2014
212014
Simultaneously linking entities and extracting relations from biomedical text without mention-level supervision
T Bansal, P Verga, N Choudhary, A McCallum
Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7407-7414, 2020
182020
Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning
T Bansal, S Alzubi, T Wang, JY Lee, A McCallum
First Conference on Automated Machine Learning (Main Track), 2022
162022
A moment in the sun: Solar nowcasting from multispectral satellite data using self-supervised learning
AS Bansal, T Bansal, D Irwin
Proceedings of the thirteenth ACM international conference on future energy …, 2022
82022
Self-supervised learning on multispectral satellite data for near-term solar forecasting
AS Bansal, T Bansal, D Irwin
International Conference on Machine Learning (ICML 2021) Workshop on …, 2021
42021
Simultaneously Self-Attending to Text and Entities for Knowledge-Informed Text Representations
D Thai, R Thirukovalluru, T Bansal, A McCallum
Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP …, 2021
22021
Relating romanized comments to news articles by inferring multi-glyphic topical correspondence
G Tholpadi, M Das, T Bansal, C Bhattacharyya
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
22015
Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models
M Das, T Bansal, C Bhattacharyya
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Articles 1–20